Propositions 20 & 27 both address redistricting. 20 moves the congressional redistricting responsibility from the legislature to the Citizens Redistricting Commission (created in 2008 by prop 11 for state districts, as opposed to federal districts). 27 would instead repeal prop 11 and move redistricting responsibility back to the legislature entirely.
The CRC is made up of 14 registered voters who apply for a position on the commission. It convenes once every 10 years after each census to perform redistricting.
Only one of 20 and 27 will be implemented. If both pass, the one receiving more “yes” votes will be implemented.
To me it appears the CRC is designed to reduce the effect of gerrymandering by the elected officials. If the representatives aren’t involved in redistricting anymore then they can’t conveniently modify their district to make it easier to stay elected. The CRC has a strict set of criteria that must be followed when creating districts which are not required under current law when the legislature controls redistricting.
I’ll probably be voting in favor of 20 and against 27.
The CRC is supposed to try and maintain (as much as possible) neighborhoods and “communities of interest” which has been defined as “a contiguous population which shares common social and economic interests that should be included within a single district for purposes of its effective and fair representation.” The Pro-27 argument tries to say (without saying) that prop 20 is racist because of this clause. That by keeping a socio-economic population together in a district they’ll be disenfranchised (but they don’t really explain how). I’m not buying this argument since when kept as a district they’re basically guaranteed representation. The alternative allows such a population to be split apart into neighboring districts where they might end up being the minority in each of those districts. In which case they will definitely be disenfranchised.
I think of political districts like a machine learning clustering algorithm. You don’t want your clusters to have large chunks of unrelated data, especially when otherwise cohesive data gets split across several other clusters. That cohesive data should represent its own cluster. I think political districts should be treated similarly. Otherwise you get a definitely skewed representation rather than a possibly skewed representation.
In fact, there’s really no reason I can think of that redistricting couldn’t be performed by a fairly simple machine learning algorithm. It wouldn’t really be very difficult to feed in your parameters (the set of rules which the CRC must follow) and let the computer spit out your new districts. The code used could be published and anyone could potentially review the process and determine if there was any intentional bias introduced into the system.
